New AI Robots Are Being Used To Predict When You Die With 90% Accuracy, But That Is Not The Scariest Part

Robots are going to be the next great technological change of the 21st century. However, what will these changes look like? Some of them are outright disturbing, especially with the rise of “AI”, or “artificial intelligence” that matches and many times, surpasses what a human can do and with disturbing accuracy, such as one AI recently developed that allegedly can tell with up to 90% accuracy when a patient in the hospital will die:

Stanford researchers have developed an AI that can predict when a patient will die with up to 90 percent accuracy.

While the idea might sound unnerving, the team behind the work says it could vastly improve end-of-life care for patients and their families.

By more accurately pinpointing when a terminal or seriously ill patient may pass, caregivers can prioritize their wishes and ensure important conversations are held before it’s too late.

In the new study published pre-print to arXiv, the Stanford team explains that there is often a huge discrepancy between the way a patient wants to live out the rest of their life, and how it actually happens.

According to the researchers, roughly 80 percent of Americans wish to spend their final days at home – but, as many as 60 percent end up dying in the hospital.

In effort to close the gap, the team at Stanford University trained a deep neural network on Electronic Health Record data from the Stanford Hospital and Lucile Packard Children’s hospital, encompassing roughly 2 million adult and child patients, according to IEEE Spectrum.

‘We could build a predictive model using routinely collected operational data in the healthcare setting, as opposed to a carefully designed experimental study,’ Anand Avati, a PhD candidate in computer science at the AI Lab of Stanford University, told IEEE.

‘The scale of data available allowed us to build an all-cause mortality prediction model, instead of being disease or demographic specific.’

The tool isn’t designed to work by itself to guide the care process.

Instead, it could be used in conjunction with assessments by the human doctor to make proactive decisions in pre-screening patients for end-of-life planning.

As the researchers explain, it isn’t always easy to understand who needs palliative care and when.

‘The criteria for deciding which patients benefit from palliative care can be hard to state explicitly,’ the authors explain in the paper.

‘Our approach uses deep learning to screen patients admitted to the hospital to identify those who are most likely to have palliative care needs.

‘The algorithm addresses a proxy problem – to predict the mortality of a given patient within the next 12 months – and use that prediction for making recommendations for palliative care referral.’

While the process may be helpful, there is one challenge – based on the ‘black box’ nature of the algorithm, the researchers don’t know exactly what its predictions are based on.

In this type of application, however, they say knowing why it made the predictions isn’t necessarily important.

‘The palliative care intervention is not tied to why somebody is getting sick,’ research scientist Kenneth Jung told IEEE.

‘If it was a different hypothetical case of “somebody is going to die and we need to pick treatment options,” in that case we do want to understand the causes because of the treatment.

‘But in this setting, it doesn’t matter as much as long as we get it right.’ (source)

Nothing good is going to come from this.

As we have noted, the robots are going to be the next major “revolution” that will change the world just as how inventions such as the printing press, industrialization, and the Internet did. The change is going to be massive. However, whereas past changes generally helped people live better lives, this change is likely not going to be for the better. It is such a radical change that it has the potential to forever alter, or perhaps permanently destroy civilization as we know it because the changes will be so drastic.

The two largest areas where the change is visible already at an early stage yet has had massive impacts are in the two enterprises which humans of all cultures will engage in regardless of population size, development, intellectual capability, or other designation. These two categories are reproduction and warfare, for they represent the two most primal impulses of man that have defined every civilization in some notable way since the beginning of human history.

The effects the robots are having on human reproduction is already massive, and it is coming in the form of “sex robots.” The robot and AI combination is the final phase of the sexual revolution because it is the complete separation of man from woman from the sexual act. The first feminist wave allowed for the possibility to consider the separation of generation from union. The second feminist wave separated generation from union, reducing sex to a glorified form of mutual masturbation. The third stage, which is really getting started now, is the separation of women from men so that pleasure is derived solely through stimuli provided by robotics or AI, thus making sexual activity a purely selfish endeavor for one’s own end tailored to one’s lusts as a man has a suit tailored to his body type. As I wrote in 2016:

But moving beyond desire, as mentioned above, sex robots will become life companions that people will interact with, form relationships with, and even get married to. Marriage itself will be redefined by the governments to include robots, such as in the awful move A.I.. Sex robots will eventually cease to be referred to as “sex robots” and referred to as “life companions,” and with enough time, they will be referred to as people and given human rights and treated as men are, which will have another effect even more long reaching, since it will allow for the definition of “humanity” to be re-defined by the government.

This is an incredibly dangerous road. If fertility rates are low right now, the sex robot will cause, worldwide, and absolute fertility collapse in all peoples, since sex affects all men regardles of race or place. Women will find themselves competing with a fantasy found in a machine to realize the unattainable, which is the perfect form. Men will to the same, pursuing the perfect vision of their pleasure, and for every woman that there may be, a better robot can be made to replace her.

Remember how in the West corporations outsource work to third world nations and destroy their local economy while benefiting a few? This is the outsourcing of sexuality to robots, thereby collapsing male-female relationships and creating a dystopic world in which pleasure is the rule and families are the rarity since people would rather pursue their fantasy through sex rather than use sex for its created purpose.Families will exist by choice, not by natural events. It will further isolate and again, make marriage something done by choice, not natural action. It will destroy the conception men and women have of each other by offering them a pleasure they cannot naturally have easily and everywhere, thus making human sex boring. Machine sex will pervert the very institution of sex itself and immerse mankind in an ocean of sterile hedonism. The sex robot will be worse than the scourge of homosexuality, because it will even obviate the current state of homosexual relations, since now instead of exposing oneself to disease a sodomite can give himself a personal harem of robots that he can sodomize and be sodomized by without the risk of disease or the trouble of a relationship with another men (and for those who know gay men, which often end bitter or violently).

If a man can derive all the pleasure he wants from a machine or machines made to his liking, the incentive to reproduce with a woman no longer exists unless made by conscious, deliberate choice. There is no more natural reasons for generation, and as water follows the path of least resistance, so will the human race follow the robot into what the Danish eugenicist Helmuth Nyborg calls “positive eugenics,” which is when a subject that ones desires to prevent from reproducing engages in behaviors that achieve this end without violent means (this is opposed to what Nyborg calls “negative eugenics,” which is the destruction of a subject by force applied from a person who is not the subject).

Already the sex robots have generated tremendous interest worldwide. Brothels have been trying them and the robots are more popular with customers than real prostitute to such an extent that prostitutes are, for the first time in history, being forced to seek work other than the “world’s oldest profession”, which I wrote about last year:

The unusual story of “Fanny”, a sex doll which has become the top-selling superstar of the “Kontakthof” brothel in the Austrian capital of Vienna, became worldwide news in July with newspapers all over the world telling the tale of how she got more customers than the prostitutes.

Now Austrian media are reporting that a growing number of other brothels are making the switch to include sex dolls.

Peter Laskaris, who operates two brothels in Vienna, said that although life-like dolls from Japan “cost up to 7,000 EUR” (6,382 GBP) it is “obviously a trendy sex fetish” which other brothels must also follow.

Kontakthof, which rents out sex doll Fanny for 80 EUR (72.9 GBP) per hour, is now considering buying a second sex doll due to the huge demand as Fanny is often completely booked for several days in a row. (source, source)

Sex robots are already changing the face of human reproduction, and this is at an infantile stage. What will it look like when these robots go from rubber skin to being covered in living tissue so they are indistinguishable from a human, such as was the character played by Arnold Schwartzenegger in the famous James Cameron film Terminator? The popularity will only continue to grow.

The changes which robots bring to the bedroom is going to be magnified even more outside the bedroom. I speak here of the use of robots for military purposes, of which the uses are endless. As we have reported exclusively at, the reason for the existence of abortion is only in part a form of eugenics, because the dead baby body parts collected from the gruesome procedure contain large numbers of certain cells used in human development which are being sold to major scientific companies, technology companies, university laboratories, and research firms backed by money coming from governments and banks around the world in the race to develop a new field of biotechnology with two distinct points of focus.

On one hand there is the desire to create “cures” for advanced forms of genetic therapy, usually funded by billionaires in the technology industry who want to be able to create a way to “change out” body parts as they age just as one changes the parts on a car so to expand the duration of their lives. On the other hand there are companies who are using the same parts to develop living tissue covers for robots just like that which I mentioned about Terminator, except instead of looking like sexy women, these will be used for the purpose of creating armies of super soldiers that will change war in the same way the machine gun and atom bomb did. These robots have already declared that they want to destroy humans multiple times, and the Pentagon has admitted they want to possess Terminator-style robots that are capable of EATING people as a source of energy:

The name of the robotic project is called the Energetically Autonomous Tactical Robot, nicknamed EATR, which is being developed by Robot Technology, Inc. RTI is a Maryland-based company which “provides systems and services in the fields of intelligent systems, robotic vehicles (including unmanned ground, air, and sea vehicles), robotics and automation, weapons systems, intelligent control systems, intelligent transportation systems, intelligent manufacturing, and other advanced technology for government, industry, and not-for-profit clients.” (source). RTI’s work has been praised by the Brookings institute and Peter Singer since at least 2009, who we have written about are pushing for the development of killer robots. They even recommend a book by Singer, called Wired for War: The Robotics Revolution and Conflict in the 21st century.

According to its website, the EATR Project:

he purpose of the Energetically Autonomous Tactical Robot (EATR)™ (patent pending) project is to develop and demonstrate an autonomous robotic platform able to perform long-range, long-endurance missions without the need for manual or conventional re-fueling, which would otherwise preclude the ability of the robot to perform such missions. The system obtains its energy by foraging – engaging in biologically-inspired, organism-like, energy-harvesting behavior which is the equivalent of eating. It can find, ingest, and extract energy from biomass in the environment (and other organically-based energy sources), as well as use conventional and alternative fuels (such as gasoline, heavy fuel, kerosene, diesel, propane, coal, cooking oil, and solar) when suitable. (source, source)

The future of warfare does not lay with humans, but with the machines they are able to build. In a certain sense this already exists with much of the advanced technology at the disposal of the military, but this will become even more profound with the robots, for the robot is the literal replacement to the foot soldier. Soldiers no matter how well trained they are still are people. They need food, water, sleep, social interaction, can have mental problems, can make decisions contrary to what they are told to, can be tortured, and can die. A machine that appears as a man will be able to deceive most men and will possess the strength of a steel machine, the ability to function without rest, food, social interaction, or water, can function in the most extreme conditions on minimal expendature for energy in ways that would be impossible for men to function under, they cannot be tortured, and they cannot die, but just break. In a practical military sense, they solve problems that armies of all cultures have been trying to solve but cannot since the first human conflict until now.

These two aspects should be terrifying enough, but the reality is they are just the most visible. Robots will eventually come to redefine all aspects of human life because it is a human surrogate. Since a machine will always be more efficient than a human, if a machine can be made to imitate the tasks which a human already does, than what purpose do humans have in a world dominated by tasks performed by robotics? This is especially pertinent in terms of “manual labor,” since the majority of people do not have intensive education in highly specialized areas performing critical tasks that only a human can perform for now. Most do jobs that could be, theoretically, replaced by a semi-advanced robot, and even possibly some of the robotics models currently on the market. Some reports say that within a decade, over 800 million jobs worldwide, or just over 10% of the world’s population- not even the global work force, which would make the percentages higher- would be lost to machines of various types:

A new study by the McKinsey Global Institute estimates that between 400 million and 800 million of today’s jobs will be automated by 2030.

The research adds fresh perspective to what is becoming an increasingly concerning picture of the future employment landscape. “We’re all going to have to change and learn how to do new things over time,” institute partner Michael Chui told Bloomberg.

In the U.S., it seems it’s the middle class that has the most to fear, with office administrators and construction equipment operators among those who may lose their jobs to technology or see their wages depressed to keep them competitive with robots and automated systems.

In places where labor is cheaper and tech is more expensive, jobs may be less vulnerable than in more developed markets.

There will—of course—be new kinds of jobs, too, McKinsey’s research arm said. As recently articulated by business leaders like Bill Gates and Autodesk chief Andrew Anagnost, an aging population may lead to more work for caregivers (unless they too are replaced by robots, as is happening in Japan) and for people who tend to the robots.

“There will be enough jobs for all of us in most scenarios,” report co-author Susan Lund said, according to Wired. (source)

Now while “middle class” jobs are identified as being affected greatly, the result will be a large elimination followed by a severe reduction in wages. Those who have the most to fear for are the poor as the skills that many poor people have are those in some kind of basic manual labor, and those are already being replaced right now:

Some of the robots used at Amazon. This video is from 2016, and the fact is that even more advanced robots exist now. This is the future of logistics and many other jobs, as they will be taken over by automation. The big issue will be what will happen to the many people that such robots will inevitably be used to justify putting people out of work.

When large numbers of people are out of work or unable to find work, then trouble happens. In cities and communities it means gang violence and local conflict. When entire societies are involved, this means war. As we have noted on, there is a revivalism of nationalism taking place that in conjunction with weapons advances, especially those of AI, are preparing the way for a coming future conflict.

But in my opinion, that is not even the scariest part of the rise of AI. So if the mass loss of jobs, eugenics, and war are not enough to disturb me, than what is?

It’s the part that I highlighted earlier in the article (go back up and look). It’s the fact that the scientists admit they have no idea how AI actually works.

This is not the first time that scientists have said this either, and they openly admit that it is the darkest secret of the brightest minds who work in AI, that they have NO IDEA how it functions, such as is reported by MIT’s Technology Review:

Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it.

Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result seems to match the responses you’d expect from a human driver. But what if one day it did something unexpected—crashed into a tree, or sat at a green light? As things stand now, it might be difficult to find out why. The system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single action. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.

The mysterious mind of this vehicle points to a looming issue with artificial intelligenceThe car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will. That’s one reason Nvidia’s car is still experimental.

Already, mathematical models are being used to help determine who makes parole, who’s approved for a loan, and who gets hired for a job. If you could get access to these mathematical models, it would be possible to understand their reasoning. But banks, the military, employers, and others are now turning their attention to more complex machine-learning approaches that could make automated decision-making altogether inscrutable. Deep learning, the most common of these approaches, represents a fundamentally different way to program computers. “It is a problem that is already relevant, and it’s going to be much more relevant in the future,” says Tommi Jaakkola, a professor at MIT who works on applications of machine learning. “Whether it’s an investment decision, a medical decision, or maybe a military decision, you don’t want to just rely on a ‘black box’ method.”

There’s already an argument that being able to interrogate an AI system about how it reached its conclusions is a fundamental legal right. Starting in the summer of 2018, the European Union may require that companies be able to give users an explanation for decisions that automated systems reach. This might be impossible, even for systems that seem relatively simple on the surface, such as the apps and websites that use deep learning to serve ads or recommend songs. The computers that run those services have programmed themselves, and they have done it in ways we cannot understand. Even the engineers who build these apps cannot fully explain their behavior.

This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.

In 2015, a research group at Mount Sinai Hospital in New York was inspired to apply deep learning to the hospital’s vast database of patient records. This data set features hundreds of variables on patients, drawn from their test results, doctor visits, and so on. The resulting program, which the researchers named Deep Patient, was trained using data from about 700,000 individuals, and when tested on new records, it proved incredibly good at predicting disease. Without any expert instruction, Deep Patient had discovered patterns hidden in the hospital data that seemed to indicate when people were on the way to a wide range of ailments, including cancer of the liver. There are a lot of methods that are “pretty good” at predicting disease from a patient’s records, says Joel Dudley, who leads the Mount Sinai team. But, he adds, “this was just way better.”

At the same time, Deep Patient is a bit puzzling. It appears to anticipate the onset of psychiatric disorders like schizophrenia surprisingly well. But since schizophrenia is notoriously difficult for physicians to predict, Dudley wondered how this was possible. He still doesn’t know. The new tool offers no clue as to how it does this. If something like Deep Patient is actually going to help doctors, it will ideally give them the rationale for its prediction, to reassure them that it is accurate and to justify, say, a change in the drugs someone is being prescribed. “We can build these models,” Dudley says ruefully, “but we don’t know how they work.”

Artificial intelligence hasn’t always been this way. From the outset, there were two schools of thought regarding how understandable, or explainable, AI ought to be. Many thought it made the most sense to build machines that reasoned according to rules and logic, making their inner workings transparent to anyone who cared to examine some code. Others felt that intelligence would more easily emerge if machines took inspiration from biology, and learned by observing and experiencing. This meant turning computer programming on its head. Instead of a programmer writing the commands to solve a problem, the program generates its own algorithm based on example data and a desired output. The machine-learning techniques that would later evolve into today’s most powerful AI systems followed the latter path: the machine essentially programs itself.

He also has a word of warning about the quest for explainability. “I think by all means if we’re going to use these things and rely on them, then let’s get as firm a grip on how and why they’re giving us the answers as possible,” he says. But since there may be no perfect answer, we should be as cautious of AI explanations as we are of each other’s—no matter how clever a machine seems. “If it can’t do better than us at explaining what it’s doing,” he says, “then don’t trust it.” (source)

How interesting. The scientists who build AI do not understand what the AI does, how it programs itself, how it “learns,” or how it functions. Essentially, it is a person who is not a person, a brain with all the physical capacities of a human brain and more but without a soul. Place the “brain” into a robot, and now you have for all intensive purposes a direct replica of a person who can do all that a person can do but who lacks a soul.

The robot/AI combination has been able to, from what we can see, to accomplish that which human cloning was unable to do.

Now it would seem very dangerous to have such a thing, for while AI is capable of doing many amazing and good things, the fact that it directly mirrors all that which a man can do even down to having the form and likeness of a man and is, really, a human surrogate. Which brings me to a very ancient concept found in pagan religion, which is the concept of the Nkisi.

In African paganism, the nkisi is an object onto which a spirit is called down and is “attached” to through the performance of a ritual. After which, wherever the nkisi goes, the spirit follows like a dog on a leash, and it is from this that a person who wants to work “magic”, such as a witch, can harness the power of the spirit attached to the nkisi for a particular end.

The Catholic Church has spoken of this issue as well, warning people about how spirits can be attached to objects and harass people. It is the reason why objects are blessed, as the blessing is an exorcism meant to cleanse an object from a presence that another person has attached to it.

So drawing on this knowledge, what is to say that a robot cannot act as a type of nkisi through the performance of a ritual that attaches a demon to it?

We know for a historical fact that some American advanced weapons and research projects had people who were deeply involved in the occult. Jack Parsons, who worked in and made major developments with rocketry including working with the infamous Nazi scientist Wernher von Braun was a devout follower of Aleister Crowley and a satanist. Col. Michael Aquino of the US military, who was an expert in psychological warfare, was a member of the church of Satan, close friends with Anton Lavey, and later founded his own satanic group, the Temple of Set, and it is even said he performed rituals at Wewelsburg Castle in the tradition of the Nazi occultist Heinrich Himmler. The Nazis, many who were brought over to the USA as a part of Operation Paperclip under the umbrella of Gladio, freely admitted and confirmed that which was being reported by sources critical of Hitler’s Reich in the early days, which is that the Third Reich’s research was deeply tied to the occult. The CIA, Defense Department, and DARPA likewise admitted to being involved in research into the occult from at least the 1950s through 1995.

If Operation Gladio, which we have written about, was the transfer of Nazi technology, methods, and philosophy to the USA, then naturally the occultism which permeated all aspects of National Socialism also had to follow.

This is just the information that we know about. Surely, there is probably far more that has actually taken place.

Likewise, we also know that the robots and robotics technology are being constructed under the umbrella of Gladio, and by the same groups who engaged in these occult experiments for decades.

We know that abortion and satanism go hand-in-hand. Abortion is one of the most heinous sins a man can commit, and as we exclusively exposed on, the abortion industry exists in order to fund the medical research being used to create the advanced robots that the AI will be used in by governments, including those of the USA, Germany, and Japan. This was the true scandal whose face was broached by the Center for Medical Progress in 2015 with proving the existence of major businesses trafficking in aborted children and which we connected in future articles.

Again, this cannot be definitively proven at the time, but given the history of the US military’s advanced research experimenting with occultism and the fact that the robotics research is being driven by said advanced research, that the robots represent a human surrogate more perfect in function  than any human clone but without a soul, that the scientists who develop AI have no idea how AI actually works, and that history repeats itself and concepts remain consistent between times and cultures, one must leave open the possibility that much of this advanced AI is simply another form of the nkisi, except that instead of it being a man in the jungle with a little wooden idol it is a full-sized robot made in a factory by men in suits and spectacles.

I’m talking about the possibility of demon-possessed robots. And I’m not joking either.

I emphasize that I am not saying “this is what this is.” What I’m saying is that something is very wrong with how this entire field of technology is developing, and that there may be more than natural forces at work here.

After all that has happened, anything is possible. It is all the more reason to return to God and prepare oneself, because one cannot possibly comprehend the true magnitude of that which is being prepared for the future…